Abstract

Abstract.

As part of the Integrated National Adaptation Pilot project and the Integrated Surveillance and Control System, the Colombian National Institute of Health is working on the design and implementation of a Malaria Early Warning System framework, supported by seasonal climate forecasting capabilities, weather and environmental monitoring, and malaria statistical and dynamic models. In this report, we provide an overview of the local ecoepidemiologic settings where four malaria process-based mathematical models are currently being implemented at a municipal level. The description includes general characteristics, malaria situation (predominant type of infection, malaria-positive cases data, malaria incidence, and seasonality), entomologic conditions (primary and secondary vectors, mosquito densities, and feeding frequencies), climatic conditions (climatology and long-term trends), key drivers of epidemic outbreaks, and non-climatic factors (populations at risk, control campaigns, and socioeconomic conditions). Selected pilot sites exhibit different ecoepidemiologic settings that must be taken into account in the development of the integrated surveillance and control system.

References

World Health Organization, 2001. Malaria Early Warning Systems, Concepts, Indicators and Partners: A Framework for Field Research in Africa. Geneva: World Health Organization/Roll Back Malaria/Technical Support Network for Prevention and Control of Malaria.

World Health Organization, 2004. Malaria Epidemics: Forecasting, Prevention, Early Detection and Control: From Policy to Practice. Geneva: World Health Organization.